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Ignite Your Networks!#

ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

https://raw.githubusercontent.com/pytorch/ignite/master/assets/tldr/pytorch-ignite-teaser.gif

Click on the image to see complete code

Features#

  • Less code than pure PyTorch while ensuring maximum control and simplicity

  • Library approach and no program’s control inversion - Use ignite where and when you need

  • Extensible API for metrics, experiment managers, and other components

Installation#

From pip:

pip install pytorch-ignite

From conda:

conda install ignite -c pytorch

From source:

pip install git+https://github.com/pytorch/ignite

Nightly releases#

From pip:

pip install --pre pytorch-ignite

From conda (this suggests to install pytorch nightly release instead of stable version as dependency):

conda install ignite -c pytorch-nightly

Documentation#

To get started, please, read Quick start and Concepts.

Library structure#

  • ignite: Core of the library, contains an engine for training and evaluating, most of the classic machine learning metrics and a variety of handlers to ease the pain of training and validation of neural networks.

  • ignite.contrib: The contrib directory contains additional modules that can require extra dependencies. Modules vary from TBPTT engine, various optimisation parameter schedulers, experiment tracking system handlers and a metrics module containing many regression metrics.


© Copyright 2021, PyTorch-Ignite Contributors. Last updated on 06/21/2020, 9:47:14 PM.

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